41 resultados para pacs: data handling techniques
Resumo:
The order Scorpiones is one of the most cytogenetically interesting groups within Arachnida by virtue of the combination of chromosome singularities found in the 59 species analyzed so far. In this work, mitotic and meiotic chromosomes of 2 species of the family Bothriuridae were detailed. This family occupies a basal position within the superfamily Scorpionoidea. Furthermore, review of the cytogenetic data of all previously studied scorpions is presented. Light microscopy chromosome analysis showed that Bothriurus araguayae and Bothriurus rochensis possess low diploid numbers compared with those of species belonging to closely related families. Gonadal cells examined under light and in transmission electron microscopy revealed, for the first time, that the Bothriuridae species possess typical monocentric chromosomes, and male meiosis presented chromosomes with synaptic and achiasmatic behavior. Moreover, in the sample of B. araguayae studied, heterozygous translocations were verified. The use of techniques to highlight specific chromosomal regions also revealed additional differences between the 2 Bothriurus species. The results herein recorded and the overview elaborated using the available cytogenetic information of Scorpiones elucidated current understanding regarding the processes of chromosome evolution that have occurred in Bothriuridae and in Scorpiones as a whole.
Resumo:
In this paper we introduce a parametric model for handling lifetime data where an early lifetime can be related to the infant-mortality failure or to the wear processes but we do not know which risk is responsible for the failure. The maximum likelihood approach and the sampling-based approach are used to get the inferences of interest. Some special cases of the proposed model are studied via Monte Carlo methods for size and power of hypothesis tests. To illustrate the proposed methodology, we introduce an example consisting of a real data set.
Resumo:
Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.
Resumo:
Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.
Resumo:
Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009
Resumo:
This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.
Resumo:
Fluorescence quenching of meso-tetrakis-4-sulfonatophenyl (TPPS4) and meso-tetrakis-4-N-methylpyridil (TMPyP) porphyrins is studied in aqueous solution and upon addition of micelles of sodium dodecylsulfate (SDS), cetyltrimethylammonium chloride (CTAC), N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS) and t-octylphenoxypolyethoxyethanol (Triton X-100). Potassium iodide (KI) was used as quencher. Steady-state Stern-Volmer plots were best fitted by a quadratic equation, including dynamic (K-D) and static (K-s) quenching. Ks was significantly smaller than K-D. Frequency-domain fluorescence lifetimes allowed estimating bimolecular quenching constants, k(q). At 25 degrees C, in aqueous solution, TMPyP shows k(q), values a factor of 2-3 higher than the diffusional limit. TPPS4 shows collisional quenching with pH dependent k(q) values. For TMPyP quenching results are consistent with reported binding constants: a significant reduction of quenching takes place for SDS, a moderate reduction is observed for H PS and almost no change is seen for Triton X-100. Similar data were obtained at 50 C. For CTAC-TPPS4 system an enhancement of quenching was observed as compared to pure buffer. This is probably associated to accumulation of iodide at the cationic micellar interface. The attraction between CTAC headgroups and 1(-), and repulsion between SDS and 1(-), enhances and reduces the fluorescence quenching, respectively, of porphyrins located at the micellar interface. The small quenching of TPPS4 in Triton X-100 is consistent with strong binding as reported in the literature. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
This paper presents the groundwater favorability mapping on a fractured terrain in the eastern portion of Sao Paulo State, Brazil. Remote sensing, airborne geophysical data, photogeologic interpretation, geologic and geomorphologic maps and geographic information system (GIS) techniques have been used. The results of cross-tabulation between these maps and well yield data allowed groundwater prospective parameters in a fractured-bedrock aquifer. These prospective parameters are the base for the favorability analysis whose principle is based on the knowledge-driven method. The mutticriteria analysis (weighted linear combination) was carried out to give a groundwater favorabitity map, because the prospective parameters have different weights of importance and different classes of each parameter. The groundwater favorability map was tested by cross-tabulation with new well yield data and spring occurrence. The wells with the highest values of productivity, as well as all the springs occurrence are situated in the excellent and good favorabitity mapped areas. It shows good coherence between the prospective parameters and the well yield and the importance of GIS techniques for definition of target areas for detail study and wells location. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.
Resumo:
The structure of chemically prepared poly-p-phenylenediamine (PpPD) was investigated by Resonance Raman (RR), FTIR, UV-VIS-NIR, X-ray photoelectron (XPS), X-ray Absorption at Nitrogen K edge (N K XANES), and Electron paramagnetic Resonance (EPR) spectroscopies. XPS, EPR and N K XANES data reveal that polymeric structure is formed mainly by radical cations and dication nitrogens. It excludes the possibility that PpPD chains have azo or phenazinic nitrogens, as commonly is supposed in the literature. The RR spectrum of PpPD shows two characteristic bands at 1527 cm(-1) and 1590 cm(-1) that were assigned to nu C=N and nu C=C of dication units, respectively, similar to polyaniline in pernigraniline base form. The presence of radical cations was confirmed by Raman data owing to the presence of bands at 1325/1370 cm(-1), characteristic of nu C-N of polaronic segments. Thus, all results indicate that PpPD has a doped PANT-like structure, with semi-quinoid and quinoid rings, and has no phenazinic rings, as observed for poly-o-phenylenediamine. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.